Shuwei Chen | University of Ulster (original) (raw)

Papers by Shuwei Chen

Knowledge-Based Systems, Jan 1, 2011

Lattice Decision support system Multi-agent system Knowledge-based system l ⁄ -Module Mixed strat... more Lattice Decision support system Multi-agent system Knowledge-based system l ⁄ -Module Mixed strategy a b s t r a c t Game theory has been applied extensively to interpret and solve the complex and interrelated practical decision problems. The solution for these problems depends on the goals pursued by different interested parties, i.e., problems as conflict situations. Decision making approaches based on game theory have been an important and promising research direction in decision science, as well as in real-world practice. Many research approaches within this direction have been developed, but most are limited to the real-valued domain. A great amount of non-real valued domain practical game decision problems, especially the lattice-valued game, remain largely unexplored. This paper investigates the lattice-valued matrix game (including the real-valued matrix game as a special case). For decision purposes, it is an essential and indispensable step in theoretical game decision approaches to find the solutions for a matrix game; hence this work focuses on how to determine solutions of lattice-valued matrix game for decision purposes. Firstly, based on the work on lattice-valued matrix game with pure strategy, a concept of multidimension lattice-valued-level strategy is introduced based on a new algebra structure called the l ⁄ -module, i.e., a lattice-ordered module with two lattice-ordered structures. Next, a concept of a mixed strategy lattice-valued matrix game is introduced and its basic properties are discussed. Finally, the necessary and sufficient condition for the existence of a solution for a mixed strategy lattice-valued matrix game is discussed, along with basic properties for the solution. The approaches and results discussed are mathematical in nature and entail fundamental research in the field of intelligent decision support. They will provide important and fundamental support for the application of a theoretical game approach in rational decisions for conflict situations, and also introduce a new branch of game-theory based decision approaches by extending real-valued game theory into lattice-value game theory.

Foundations of Intelligent …, Jan 1, 2011

Computational Engineering in Systems …, Jan 1, 2006

Uncertainty reasoning is one of important directions in the research field of artificial intellig... more Uncertainty reasoning is one of important directions in the research field of artificial intelligence. Uncertainty reasoning theory and methods based on lattice-valued logic is sound in its strict logical foundation. In this paper, some methods for selecting appropriate parameters in the uncertainty reasoning process based on lattice-valued propositional logic Y6 are proposed.

Soft Computing-A Fusion of Foundations, …, Jan 1, 2011

ABSTRACT

… : proceedings of the 6th International FLINS …, Jan 1, 2004

A MODEL OF EVALUATION OF AN APPRAISEMENT SYSTEM OF HUMAN RESOURCE* XIAOHONG LIU College of manage... more A MODEL OF EVALUATION OF AN APPRAISEMENT SYSTEM OF HUMAN RESOURCE* XIAOHONG LIU College of management. Southwest University for Nationalities, Sichuan, Chengdu, 610041, China. lxhdoctor@ sina. com SHUWEI CHEN Intelligent Control Development ...

Abstract: In this paper, a model for decision-making with linguistic information is discussed bas... more Abstract: In this paper, a model for decision-making with linguistic information is discussed based on uncertainty reasoning in the framework of lattice-valued logic through an example. In this model, decision-making process is treated as an uncertainty reasoning problem, in ...

Software Engineering and …, Jan 1, 2011

This paper proposes a generic data driven inference methodology for rule-based classification sys... more This paper proposes a generic data driven inference methodology for rule-based classification systems. The generic rule base is in a belief rule base structure, where the consequent of a rule takes the belief distribution form. Other knowledge representation parameters such as the weights of both input attributes and rules are also considered in this framework. In an established rule base, the matching degree of an input between the antecedents of a rule is firstly computed to get the activation weight for the rule. Then a weighted aggregation of the consequents of activated rules is used for the inference process.

Journal of Control Theory and Applications, Jan 1, 2005

The user has requested enhancement of the downloaded file.

… : proceedings of the 6th International FLINS …, Jan 1, 2004

Granular Computing, 2005 IEEE …, Jan 1, 2005

I. INTRODUCTION S UPPORT Vector Machine (SVM) proposed by Vapnik is a new machine learning method... more I. INTRODUCTION S UPPORT Vector Machine (SVM) proposed by Vapnik is a new machine learning method basedon the Statistical Learning Theory. Statistical Learning Theory (Vapnik[1], [2]) is mainly developed to resolve the overfitting problem experienced by ...

Foundations of Intelligent Systems, Jan 1, 2012

Symbolic and Quantitative …, Jan 1, 2011

This paper presents a parameterized reasoning approach with uncertainty based on a lattice-valued... more This paper presents a parameterized reasoning approach with uncertainty based on a lattice-valued logic system. In this uncertain reasoning approach, some parameters are used to represent uncertainty arising from different sources, which is a common phenomenon in rule-based systems. In our system, reasoning with different parameter values means reasoning with different levels of belief and consistency. Some methods are presented for selecting appropriate parameter values during the uncertain reasoning process which allow us to find suitable parameter values to meet the diverse practical and theoretical requirements.

Journal of Southwest Jiaotong University, Jan 1, 2006

To describe reasoning methods such as minimizing,multiple reasoning,multi-dimensional reasoning e... more To describe reasoning methods such as minimizing,multiple reasoning,multi-dimensional reasoning etc.,corresponding rules of inference in lattice-valued propositional logic L_(vpl) are introduced.These rules are composed of two parts,semantics and syntax,and there exists ...

Systems, Man and Cybernetics, 2004 IEEE …, Jan 1, 2004

Uncertainty reasoning is one of important directions in the research field of artificial intellig... more Uncertainty reasoning is one of important directions in the research field of artificial intelligence. Uncertainty reasoning theory and methods based on lattice-valued logic is sound in its strict logical foundation. In this paper, some methods for selecting appropriate parameters in the uncertainty reasoning process based on lattice-valued propositional logic Y6 are proposed.

Fifth International Conference on Fuzzy …, Jan 1, 2008

This paper proposes an architecture to extract fuzzy rules based on support vector machines (SVMs... more This paper proposes an architecture to extract fuzzy rules based on support vector machines (SVMs). Firstly, support vectors are obtained from the training data set to generate fuzzy IF-THEN rules with membership functions described in terms of kernel functions via support vector machine learning procedure. Then, a combined fuzzy rule base is created based on both the generated rules and linguistic rules of human experts. Thus, it has the inherent advantages that the rule base is optimized automatically during the SVM learning procedure, and, takes both "subjective" experts' prior knowledge and "objective" training data into account. An example is given to show the effectiveness of the proposed method.

Fuzzy Systems and Knowledge Discovery, Jan 1, 2005

The subject of this work is to establish a mathematical framework that provide the basis and tool... more The subject of this work is to establish a mathematical framework that provide the basis and tool for uncertainty reasoning based on linguistic information. This paper focuses on a flexible and realistic approach, i.e., the use of linguistic terms, specially, the symbolic approach acts by direct computation on linguistic terms. An algebra model with linguistic terms, which is based on a logical algebraic structure, i.e., lattice implication algebra, is applied to represent imprecise information and deals with both comparable and incomparable linguistic terms (i.e., non-ordered linguistic terms). Within this framework, some inferential rules are analyzed and extended to deal with these kinds of lattice-valued linguistic information.

… Advances and Applications of Fuzzy Logic …, Jan 1, 2007

1 Department of Mathematics, Southwest Jiaotong University, Chengdu, Sichuan 610031, PR China xuy... more 1 Department of Mathematics, Southwest Jiaotong University, Chengdu, Sichuan 610031, PR China xuyang@home.swjtu.edu.cn 2 School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan 450001, PR China swchen@zzu.edu.cn 3 School of ...

Computational Engineering in Systems …, Jan 1, 2006

The subject of this work is to establish a mathematical framework that provides the basis and too... more The subject of this work is to establish a mathematical framework that provides the basis and tool for automated reasoning and uncertainty reasoning based on linguistic information. This paper focuses on a flexible and realistic approach, i.e., the use of linguistic terms, specially, the symbolic approach acts by direct computation on linguistic terms. An algebra model with linguistic terms, which is based on a logical algebraic structure, i.e., lattice implication algebra, is constructed and applied to represent imprecise information and deal with both comparable and incomparable linguistic terms (i.e., non-ordered linguistic terms). Some properties and its substructures of this algebraic model are discussed.

Knowledge-Based Systems, Jan 1, 2011

Lattice Decision support system Multi-agent system Knowledge-based system l ⁄ -Module Mixed strat... more Lattice Decision support system Multi-agent system Knowledge-based system l ⁄ -Module Mixed strategy a b s t r a c t Game theory has been applied extensively to interpret and solve the complex and interrelated practical decision problems. The solution for these problems depends on the goals pursued by different interested parties, i.e., problems as conflict situations. Decision making approaches based on game theory have been an important and promising research direction in decision science, as well as in real-world practice. Many research approaches within this direction have been developed, but most are limited to the real-valued domain. A great amount of non-real valued domain practical game decision problems, especially the lattice-valued game, remain largely unexplored. This paper investigates the lattice-valued matrix game (including the real-valued matrix game as a special case). For decision purposes, it is an essential and indispensable step in theoretical game decision approaches to find the solutions for a matrix game; hence this work focuses on how to determine solutions of lattice-valued matrix game for decision purposes. Firstly, based on the work on lattice-valued matrix game with pure strategy, a concept of multidimension lattice-valued-level strategy is introduced based on a new algebra structure called the l ⁄ -module, i.e., a lattice-ordered module with two lattice-ordered structures. Next, a concept of a mixed strategy lattice-valued matrix game is introduced and its basic properties are discussed. Finally, the necessary and sufficient condition for the existence of a solution for a mixed strategy lattice-valued matrix game is discussed, along with basic properties for the solution. The approaches and results discussed are mathematical in nature and entail fundamental research in the field of intelligent decision support. They will provide important and fundamental support for the application of a theoretical game approach in rational decisions for conflict situations, and also introduce a new branch of game-theory based decision approaches by extending real-valued game theory into lattice-value game theory.

Foundations of Intelligent …, Jan 1, 2011

Computational Engineering in Systems …, Jan 1, 2006

Uncertainty reasoning is one of important directions in the research field of artificial intellig... more Uncertainty reasoning is one of important directions in the research field of artificial intelligence. Uncertainty reasoning theory and methods based on lattice-valued logic is sound in its strict logical foundation. In this paper, some methods for selecting appropriate parameters in the uncertainty reasoning process based on lattice-valued propositional logic Y6 are proposed.

Soft Computing-A Fusion of Foundations, …, Jan 1, 2011

ABSTRACT

… : proceedings of the 6th International FLINS …, Jan 1, 2004

A MODEL OF EVALUATION OF AN APPRAISEMENT SYSTEM OF HUMAN RESOURCE* XIAOHONG LIU College of manage... more A MODEL OF EVALUATION OF AN APPRAISEMENT SYSTEM OF HUMAN RESOURCE* XIAOHONG LIU College of management. Southwest University for Nationalities, Sichuan, Chengdu, 610041, China. lxhdoctor@ sina. com SHUWEI CHEN Intelligent Control Development ...

Abstract: In this paper, a model for decision-making with linguistic information is discussed bas... more Abstract: In this paper, a model for decision-making with linguistic information is discussed based on uncertainty reasoning in the framework of lattice-valued logic through an example. In this model, decision-making process is treated as an uncertainty reasoning problem, in ...

Software Engineering and …, Jan 1, 2011

This paper proposes a generic data driven inference methodology for rule-based classification sys... more This paper proposes a generic data driven inference methodology for rule-based classification systems. The generic rule base is in a belief rule base structure, where the consequent of a rule takes the belief distribution form. Other knowledge representation parameters such as the weights of both input attributes and rules are also considered in this framework. In an established rule base, the matching degree of an input between the antecedents of a rule is firstly computed to get the activation weight for the rule. Then a weighted aggregation of the consequents of activated rules is used for the inference process.

Journal of Control Theory and Applications, Jan 1, 2005

The user has requested enhancement of the downloaded file.

… : proceedings of the 6th International FLINS …, Jan 1, 2004

Granular Computing, 2005 IEEE …, Jan 1, 2005

I. INTRODUCTION S UPPORT Vector Machine (SVM) proposed by Vapnik is a new machine learning method... more I. INTRODUCTION S UPPORT Vector Machine (SVM) proposed by Vapnik is a new machine learning method basedon the Statistical Learning Theory. Statistical Learning Theory (Vapnik[1], [2]) is mainly developed to resolve the overfitting problem experienced by ...

Foundations of Intelligent Systems, Jan 1, 2012

Symbolic and Quantitative …, Jan 1, 2011

This paper presents a parameterized reasoning approach with uncertainty based on a lattice-valued... more This paper presents a parameterized reasoning approach with uncertainty based on a lattice-valued logic system. In this uncertain reasoning approach, some parameters are used to represent uncertainty arising from different sources, which is a common phenomenon in rule-based systems. In our system, reasoning with different parameter values means reasoning with different levels of belief and consistency. Some methods are presented for selecting appropriate parameter values during the uncertain reasoning process which allow us to find suitable parameter values to meet the diverse practical and theoretical requirements.

Journal of Southwest Jiaotong University, Jan 1, 2006

To describe reasoning methods such as minimizing,multiple reasoning,multi-dimensional reasoning e... more To describe reasoning methods such as minimizing,multiple reasoning,multi-dimensional reasoning etc.,corresponding rules of inference in lattice-valued propositional logic L_(vpl) are introduced.These rules are composed of two parts,semantics and syntax,and there exists ...

Systems, Man and Cybernetics, 2004 IEEE …, Jan 1, 2004

Uncertainty reasoning is one of important directions in the research field of artificial intellig... more Uncertainty reasoning is one of important directions in the research field of artificial intelligence. Uncertainty reasoning theory and methods based on lattice-valued logic is sound in its strict logical foundation. In this paper, some methods for selecting appropriate parameters in the uncertainty reasoning process based on lattice-valued propositional logic Y6 are proposed.

Fifth International Conference on Fuzzy …, Jan 1, 2008

This paper proposes an architecture to extract fuzzy rules based on support vector machines (SVMs... more This paper proposes an architecture to extract fuzzy rules based on support vector machines (SVMs). Firstly, support vectors are obtained from the training data set to generate fuzzy IF-THEN rules with membership functions described in terms of kernel functions via support vector machine learning procedure. Then, a combined fuzzy rule base is created based on both the generated rules and linguistic rules of human experts. Thus, it has the inherent advantages that the rule base is optimized automatically during the SVM learning procedure, and, takes both "subjective" experts' prior knowledge and "objective" training data into account. An example is given to show the effectiveness of the proposed method.

Fuzzy Systems and Knowledge Discovery, Jan 1, 2005

The subject of this work is to establish a mathematical framework that provide the basis and tool... more The subject of this work is to establish a mathematical framework that provide the basis and tool for uncertainty reasoning based on linguistic information. This paper focuses on a flexible and realistic approach, i.e., the use of linguistic terms, specially, the symbolic approach acts by direct computation on linguistic terms. An algebra model with linguistic terms, which is based on a logical algebraic structure, i.e., lattice implication algebra, is applied to represent imprecise information and deals with both comparable and incomparable linguistic terms (i.e., non-ordered linguistic terms). Within this framework, some inferential rules are analyzed and extended to deal with these kinds of lattice-valued linguistic information.

… Advances and Applications of Fuzzy Logic …, Jan 1, 2007

1 Department of Mathematics, Southwest Jiaotong University, Chengdu, Sichuan 610031, PR China xuy... more 1 Department of Mathematics, Southwest Jiaotong University, Chengdu, Sichuan 610031, PR China xuyang@home.swjtu.edu.cn 2 School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan 450001, PR China swchen@zzu.edu.cn 3 School of ...

Computational Engineering in Systems …, Jan 1, 2006

The subject of this work is to establish a mathematical framework that provides the basis and too... more The subject of this work is to establish a mathematical framework that provides the basis and tool for automated reasoning and uncertainty reasoning based on linguistic information. This paper focuses on a flexible and realistic approach, i.e., the use of linguistic terms, specially, the symbolic approach acts by direct computation on linguistic terms. An algebra model with linguistic terms, which is based on a logical algebraic structure, i.e., lattice implication algebra, is constructed and applied to represent imprecise information and deal with both comparable and incomparable linguistic terms (i.e., non-ordered linguistic terms). Some properties and its substructures of this algebraic model are discussed.